Discovering Translation-Worthy Languages with E-Values
Quick summary
arXiv:2609.06593v1 Announce Type: cross Abstract: Choosing when to translate multilingual documents is a central routing problem in text classification: translation can improve predictions for some languages while degrading others or adding unnecessary computation. Uniform translation and heuristic language tiers do not provide statistically controlled route selection. We introduce a language-level router based on paired e-processes that continuously compares direct and translation-assisted classification before freezing a routing policy. A familywise-controlled threshold of 280 bounds the pro
Key takeaways
- arXiv:2609.06593v1 Announce Type: cross Abstract: Choosing when to translate multilingual documents is a central routing problem in text classification: translation can improve predictions for some languages while degrading others or adding unnecessary computation.
- Uniform translation and heuristic language tiers do not provide statistically controlled route selection.
- We introduce a language-level router based on paired e-processes that continuously compares direct and translation-assisted classification before freezing a routing policy.
Why it matters
“Discovering Translation-Worthy Languages with E-Values” may affect what data AI products can use and where accountability sits. Product teams should watch compliance duties, rights holders should watch enforcement, and users should watch transparency and appeal mechanisms.
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